The field of the invention is medical imaging, and particularly, the use of medical imaging in the treatment of cancer.
Advanced imaging techniques for brain and other neoplasms acquire a variety of physiological data in addition to anatomic data. These include PET scanning, conventional MRI, MRI-spectroscopy, diffusion imaging, SPECT, perfusion imaging, functional MRI, tumor hypoxia mapping, angiogenesis mapping, blood flow mapping, cell death mapping and other methods. In addition, it is anticipated that new and better agents for use in SPECT, PET, and other imaging will be created and/or identified. These techniques will lead to an improvement in the ability to differentiate tumor from normal tissue.
Traditional display of physiologic images is in several ways insufficient. Physiologic images generated from sources such as PET and SPECT are indistinct (tumors have “blurry” borders), and are anatomically ambiguous. Fusion software has facilitated the viewing of neoplasms represented by PET and SPECT within the context of anatomic detail represented by CT. Integrated PET-CT and SPECT-CT devices have improved registration and fusion of anatomic and physiologic images. Traditionally, fused images are viewed by fading between CT and physiologic images, ranging from 0% CT/100% physiologic images, to 100% CT/0% physiologic images.
In present day treatment planning the creation of a three-dimensional treatment volume often involves the manual, slice-by-slice digital outlining of tumor on sequential tomographic images at a computer workstation. Computers are then used to convert cut-by-cut digital outlines into three-dimensional volumes, which become targets for surgical and/or radiation therapy planning. This process is labor-intensive. More importantly, however this process relies on the judgment of the person, usually a physician, digitizing the slice-by-slice images.
There are several limitations associated with the reliance on human judgment in this capacity. First, different physicians have different levels of experience in interpreting scans. Planning based on volumes generated by inexperienced physicians will be less accurate. Secondly, even for experienced physicians, interpretation of imaging findings is in many cases difficult, and in many instances based on “best guess” decision making. Even for experienced physicians, there will always be inter-observer variability. Thus, in research/protocol situations, outcomes data will not be directly transferable from institution to institution.
For imaging modalities such as spectroscopy or PET, particularly for tumors that invade adjacent structures or soft tissues, the line between tumor and adjacent non-tumorous structures is subjective and indistinct. This creates variability from cut to cut, patient to patient, and physician to physician. More importantly, however, it creates uncertainty with regard to the optimal volume needed to maximize local control while minimizing dose (and damage) to adjacent structures.
Traditional systems that display images or incorporate images into treatment processes consider images as physiologically homogenous. This is despite the fact that tumors are known to be physiologically heterogeneous. The limitations described above, related to display of a tumor's outer boundary, also apply to display of a tumor's internal heterogeneity.